Claims fraud costs U.S. insurers $308 billion a year. Let’s fix that.
From opportunistic individual fraud to organized networks, insurers face an array of claims fraud efforts. Shift enables insurers to find more fraud, empowers investigators, and improves insurers’ loss ratios.
Insurers know that better data means better fraud decisions. Partnering with Shift provides access to the best external data sources, delivering over a third increase in fraud stopped.
Global data approach
Strategic partnership strategy
Our powerful AI provides impact across the claims fraud lifecycle through data processing, machine learning, document analysis, and advanced network detection.
AI made for insurance fraud
Globally tailored scenarios
Shift’s UI provides clear context for accelerated and more efficient investigations.
KPIs & reporting
We are 100% focused on insurance and hire the industry’s best talent to provide our customers with unmatched support.
Dedicated customer success
200+ data scientists
AI & UI updates
Helping Insurers Win the Fight Against Fraud
Shift is trusted by leaders of the world’s leading insurers to effectively identify fraud and increase investigation efficiency resulting in more than $5B in claim fraud identified in 2021 alone.
Shift was built around the needs of Insurers. The use of our technology has led to drastic improvements across the claims process from insights to process. No area goes untouched.
Insurers looking to revolutionize their teams look to Shift for our expertise and partnership, enabling their organization to take performance to the next level.
Shift takes the work of your top performers, automates, optimizes, and streamlines processes increasing efficiency up to 4x.
The three pillars of data integration
Data integration is a critical component to finding more fraud, but it needs three things in order to work - ownership, retrieval, and analytics. These elements work together allowing insurers to fully access and utilize their data.
In this report, Shift's data experts discuss these three pillars of data integration and how they impact fraud detection maturity
- Ownership - Managing internal and external data
- Retrieval - Retrieving and linking data
- Analytics - Analysis automation and decision